In professional football a key factor regarding injury is the time to return to play. Accurate prediction of this would aid planning by the club in the event of injury. It would also aid the club medical staff. Gaussian processes may be used for machine learning tasks such as regression and classification. This study determines whether machine-learning methods may be used for predicting how many days a player is unavailable to play. A database of injuries at one English Premier League Professional Football Club was reviewed for a number of factors for each injury. Twenty-five variables were recorded for each injury, including time to return to play. This was determined to be the response variable. We used a Gaussian process model with a Laplacian kernel to determine whether the return to play could be predicted from the other variables. The root mean square error was 13.186 days (S.D.: 8.073), the mean absolute error was 8.192 days (S.D.:13.106) and the mean relative error 171.97% (S.D.:75.56%). A linear trend was observed and the model demonstrated high accuracy with greater errors being observed for cases where the value of the response variable was higher, i.e. in those cases where the time to return to play was lengthy. This is the first step in attempting to design a computer-based model that will accurately predict the time for a professional footballer to return to play. The model is extremely accurate for most cases, with errors increasing as the severity of the case increases too.
Patella tendonitis is common amongst sportsmen. No published evidence of this injury in elite professional footballers exists. The aim of this study was to determine the frequency of this injury in the elite professional footballer, along with the impact of such an injury on the amount of time missed and the outcomes of various treatment options. Data was collected prospectively for injuries suffered by first team players, development squad players and academy squad players over the 2009–10 and 2010–11 English Premier League (EPL) season at one EPL club. Each player's demographics were recorded. The injury was recorded along with the time that the player was absent because of the injury, the treatment that the player received and whether they suffered any recurrence of the injury.Introduction
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Knee injuries are common amongst footballers. The aim of this study was to establish frequency and variation of knee injuries within one English Premier League (EPL) professional football club over two seasons, to assess number of days missed due to injury, and analyse current treatment regimen for each injury type. Data was collected prospectively for injuries suffered by players between 2009 and 2011, spanning two EPL seasons at one EPL club. Demographics were recorded along with various factors influencing injury, including playing surface, pitch condition, dominant side, type of injury, ability to continue playing, and mechanism of injury. Time taken for return to play, and treatment received was recorded.Introduction
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Foot and ankle injuries are a common occurrence amongst all footballers. The aim of this study was to establish the frequency and variation of foot and ankle injuries within one English Premier League (EPL) professional football club over the course of a season and attempt to identify any factors associated with the injuries. Data was collected prospectively for all foot and ankle injuries suffered by first team players over the 2008–09 and 2009–10 EPL season at one EPL club. Each player's demographics were recorded along with various factors concerning or influencing the injury including ground conditions, foot posture index score (FPIS), type of injury, ability to continue playing, recovery time, mechanism of injury and footwear type.Introduction
Method
Shoulder instability is a common cause of morbidity amongst Professional Rugby Union players. This study explores whether the risk of shoulder dislocation is associated with innate shoulder laxity. A randomised controlled study was completed in which all the Premiership Rugby Clubs in England were visited in 2006. 169 professional rugby players (mean age 25.1 years) with no history of instability in either shoulder were assessed and 46 injured players with one shoulder with a history of Bankart lesion or dislocation (mean age 27.5 years) also took part in this study. Shoulder laxity was measured by dynamic ultrasound. Anterior, posterior and inferior translations were measured in both shoulders for healthy players and the uninjured shoulder only for injured players.Objective
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